In common-law systems, legal cases tend to cite one another. This Demonstration synthesizes a legal precedent structure in which cases are given up to five features as well as a time of decision. Cases cite preceding cases whose features most closely resemble themselves, with "closeness" being defined in a user-selectable manner. The cases in this Demonstration are generated using a Lévy flight model that attempts to reflect the notion that cases tend to be clustered together rather than randomly filling some "judicial space." It visualizes the Lévy flight where possible and shows the legal precedent network.

Snapshots

Details

The user can control the dimensionality and tail-parameter α of the Lévy flight, the number of cases in the legal system, the mean number of outgoing citations per case, the standard deviation of the number of outgoing citations per case, and the number of features of preceding cases examined. The default "closeness" measure says that cases are near each other if any of them resemble each other in any dimension.

Snapshot 1: three-dimensional Lévy flight

Snapshot 2: four-dimensional Lévy flight with a larger number of cases